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US chip champion Intel was so confused by the US government ban on foreign-made robots that it requested and received a waiver “out of an abundance of caution.” The tech company wanted to make sure that it could continue using certain robotic vehicles in its US chip fabs.
The uncertainty surrounding the Federal Communications Commission ban on certain foreign-made robots was revealed in the agency’s decision to grant Intel’s waiver request. On October 22, the FCC published its order allowing Intel to continue using the foreign-made robots in US semiconductor manufacturing facilities for a period of one year.
The robots in question are automated guided vehicles operating on “tracks or predefined paths” while often requiring operator oversight, according to Intel’s website. They help to move materials and items around within warehouses and factory floors.
No organization in the world operates more robots than Amazon. The company already has more than 1 million robots working in warehouses around the clock to make tens of millions of same-day and one-day package deliveries happen on a daily basis—and Amazon is poised to significantly grow that robotic fleet in the coming years as it establishes new factories to churn out increasingly more capable robot workers.
Despite deploying so many robots, Amazon is also the second-largest corporate employer in the world, with more than 1.5 million full-time and part-time human workers, according to its 2025 annual report. Amazon executives say that the growing robot fleet has eased the burden on its human workforce by taking on the toughest fulfillment center tasks that carry the greatest risks of physical fatigue and injury. But labor advocacy groups and independent researchers point to evidence suggesting that warehouse automation driven by AI is not all upside for the humans who work alongside robots.
“For the last 100 years, most of the automation that we've seen usually happens away from workers—you're taking that high-risk task away from the worker, and you're doing so in a way that is not physically proximate,” Brad Greenwood, professor of business at George Mason University, told Ars. “The rise of collaborative robots really changes that dynamic for two reasons: one is that it is physically proximate, and two, the robot has the ability to dictate the pace of work.”
Investors bullish on AI data centers may be fueling Nvidia’s multitrillion-dollar market capitalization, but the AI chipmaker has also bet billions of dollars on physical AI technologies such as robotics and self-driving cars. Part of that gambit has involved developing a full-stack safety system that companies can build upon to reduce the risk of their machines harming nearby people.
Nvidia's Halos system launched in 2025 with hardware and software tools to help developers implement guardrails in self-driving cars and other autonomous vehicles. Then the company expanded its safety architecture to more physical AI technologies by announcing Nvidia Halos for Robotics in June 2026—with the goal of enabling safe deployments of autonomous mobile robots in warehouses, humanoid robots walking around inside a factory, or even surgical robots.
“Now the AI models are getting capable, the robot hardware is getting capable, and a thing we thought is going to be the next bottleneck is safety,” Amit Goel, head of robotics ecosystem and edge computing at Nvidia, told Ars. “So that's why we launched our Halos for Robotics to unlock the capability of these systems.”
This year, members of Seattle Mountain Rescue have been setting off into the wilds of the US Pacific Northwest wearing an unusual piece of kit.
They’ve been hiking into the wilderness with powered assistive devices attached to their hips and legs. Designed to increase lower-body strength when climbing or carrying heavy loads, these pieces of equipment are being tested to see if they can boost rescuers’ speed and endurance when it matters most—during searches for stranded people.
Devices like these are called human exoskeletons. They attach to parts of the body to create an external—or “exo”—mechanical structure. This powered frame enhances the wearer’s physical capabilities.
Tesla’s pivot from making electric cars to humanoid robots is facing challenges because of complex robot hands and disgruntled employees pushing back against training their robotic replacements. The struggle to scale up production comes as Tesla CEO Elon Musk has bet the company’s future on AI and robotics.
As someone who frequently makes claims that fail to materialize, Musk has described the Optimus humanoid robot as potentially “the biggest product ever” during Tesla’s second-quarter 2026 earnings call. But he also acknowledged that making an autonomous humanoid robot capable of handling many different tasks is “one of the hardest things to solve”—and now extensive reporting by The Information has revealed multiple complications that Tesla is trying to tackle while developing general-purpose robots and scaling up for mass production.
Tesla’s Fremont factory in California has already stopped making the Model S sedan and Model X SUV as of May 2026, with the company switching both line workers and engineers over to working on Optimus, according to The Information.
Toyota workers are already helping to train humanoid robots as part of the automaker’s race to eventually deploy 400,000 factory robots—but a Toyota executive said the robotic push is not meant to directly replace humans.
Starting in 2028, the Toyota Motor group aims to start investing $6.42 billion every year in upgrading factories with the new robotic workforce, according to Nikkei Asia. The company wants to put 150,000 robots in its own automotive plants and deploy another 250,000 at group company facilities that produce various components and materials.
Toyota has already begun deploying some of its ELEY humanoid robots across assembly lines to learn from human workers. Nikkei Asia reported that workers are teaching the robots, which roll around on wheels, to perform tasks requiring precise hand movements by wearing “jigs” based on the humanoids’ fingers.
On a sunny morning in June, I walked to work with a quadruped robot beside me. I’ve never gotten more attention from strangers.
A bunch of people snapped pictures of my robot dog. Several people asked me questions. Was it mine? (Yes.) Did I build it? (No.) Was it being used for surveillance? (No.)
Biological dogs kept a safe distance from my mechanical companion. Some growled or barked at it.
Meta is testing robots that can plug in cables, reset servers, and handle other tasks inside its data centers, according to several current and former workers familiar with the projects. The ongoing effort, which has not been previously reported, may eventually allow Meta to operate its rapidly expanding data center footprint with fewer humans, keeping labor costs in check as its spending on AI infrastructure soars.
Meta is using robots and related hardware from several different vendors, including Watney Robotics, Kinova, and ABB, according to the same workers, who asked to remain anonymous because they weren’t authorized to speak to the media. Kinova and ABB declined to comment. Watney didn’t respond to requests for comment.
In one experiment, Meta is evaluating whether a Kinova Gen3 robotic arm could be used for power cycling or cutting off electricity to servers. The company is also testing a different robot to swap networking cables. One Meta data center worker estimates that if it’s successful, the bot could replace up to 80 percent of some people’s workloads. “We thought those of us performing the physical tasks were safe for a while, but not anymore,” says the worker. “It’s coming for us all, unfortunately.”
For all the interest in and uptake of agentic AI systems over the past year or so, the world of automated AI has thus far been primarily limited to text, images, code, and other data and actions that take place inside a computer. Anthropic is now aiming to change that somewhat with what it's calling the Model Hardware Standard (MHS), a set of standardized drivers designed to let AI agents easily interface with and control arbitrary devices.
For now, the "research preview" of the MHS effort is being sold mainly as a way to help scientists streamline the arduous process of creating the custom software integrations that are often needed to get disparate components of an experiment working in concert. MHS can provide a common interface and common format for data sharing between these devices, Anthropic says, allowing them to talk to each other across a network "without needing a bespoke 'translator' program in between." The standardized system could reduce weeks or months of exacting experimental setup down to "hours or minutes," Anthropic writes.
An Anthropic graphic illustrating how MHS serves as a "translation" layer between AI agents and multiple types of devices.
Credit:
Anthropic
In a video posted alongside the announcement, Anthropic Technical Staffer Alek Kemeny says the MHS effort was inspired by observing neuroscientist Arco Bast work through an experiment on memory formation in the brain at the HHMI Janelia Research Campus in Ashburn, Virginia. Kemeny said Bast had worked out an interface to get the rotating laser beams, microscopes, cameras, and myriad other components of the experiment to coordinate through a common interface. "This idea could be used to have AI run any science experiment in the world," Kemeny recalls thinking at the time.
Viral videos of the World Humanoid Robot Games show sprinting robots beating the human 100-meter record held by Usain Bolt—but also feature running robots crashing into barriers and falling down because they cannot readily stop running. A few fallen robots even break at the waist in a shower of sparks or catch on fire.
That demonstration of both robotic prowess and limitations came from the second edition of the World Humanoid Robot Games hosted in Beijing from August 22–26. Like the inaugural event held in 2025, this year’s event challenged humanoid robots to run fast, perform kung fu or dance moves, fight one another in kickboxing, and play soccer or table tennis.
This year’s games also tested robots in more humdrum practical scenarios like washing and hanging laundry, where they appeared to lag behind typical human working speeds. That suggests the event organizers, including Chinese state media and the Beijing city government, are keen to showcase the commercial potential of humanoid robots at a time when China’s robotics industry is rapidly developing and testing such robots.
A leading US distributor of China’s most popular humanoid robots and robot dogs now plans to produce its own robots at a facility on Long Island, New York. The business pivot comes amid the US government’s growing crackdown on foreign-made robots.
The company, RoboStore, had previously become the main North American distributor for humanoid robots and quadruped robots from Unitree Robotics, a Chinese robotics company that produces some of the most affordable and popular humanoid robot models. Universities like Harvard and MIT, along with tech companies like Amazon and Nvidia, purchased such robots made in China through RoboStore for their own research and development purposes.
“We’ve sold over 1,500 robots and deployed them and worked with customers like Cisco, OpenAI, Nvidia, and over 150 universities,” Teddy Haggerty, founder and CEO of RoboStore, told Ars.
Three former SpaceX engineers have switched their attention from making rocket engines to manufacturing steel parts by using AI-driven software and robots. Their immediate goal involves establishing a prototype factory that can automate most of the steel fabrication process for crucial infrastructure components by 2027.
The startup, called 1872, officially launched on July 22 with a ribbon-cutting ceremony at its Factory One facility in Cincinnati, Ohio. The company is initially focused on automating the manufacturing of steel skids—rectangular steel frames that can provide a moveable foundation for modular buildings—with the goal of supplying customers who are developing AI data centers or small modular nuclear reactors.
“We're building towards autonomy, but we're not necessarily building in a dogmatic fashion towards full autonomy,” Dan Summers, CEO of 1872, told Ars. “We may achieve 80 percent autonomous operations, and we may decide that it makes sense to stop there because there's just diminishing returns to go to full 100 percent.”
Humanoid robots and four-legged robots made in China fall squarely under a new ban imposed by the US Federal Communications Commission on foreign-made robots. But the sweeping prohibition covers a wide variety of robots manufactured anywhere abroad, including the newest robot vacuum cleaners.
The Trump administration's FCC justified the ban on foreign-made robots by referencing cybersecurity vulnerabilities previously discovered in robots specifically made by Chinese companies. On July 28, the federal agency added “foreign-produced advanced robotic devices” to its Covered List of technologies “deemed to pose an unacceptable risk to the national security of the US or the safety and security of US persons.”
However, the FCC cannot update the Covered List on its own initiative and is required by law to follow the direction of a “qualifying national security authority.” The agency describes the White House as having “convened an executive branch interagency body” that “included appropriate national security agencies,” which determined foreign-made robots as presenting a national security risk.
Robots slithered like snakes into the rubble of collapsed buildings to search for trapped survivors in the aftermath of Venezuela’s double earthquake disaster.
The so-called snake robots represented a unique technological aid for international search and rescue efforts following two earthquakes that struck Venezuela on June 24, killing more than 5,000 people and leaving behind 16,740 injured. Rescuers from around the world used trained dogs, seismic and acoustic listening devices, video cameras on sticks, or thermal imaging cameras to search for signs of survivors—but the snakebots equipped with a video camera could squeeze through tight spaces to search deep within fallen building debris.
“The reason why snake robots are useful is they can get into tightly packed volumes that machinery and people otherwise cannot, and that's important in search and rescue because we were able to extend the visual reach of the rescue workers in a safe way,” Howie Choset, head of the Biorobotics Lab at Carnegie Mellon University in Pittsburgh, told Ars. “In a sense, you're doing minimally invasive surgery on a structure with a snake robot.”
Hyundai Motor Company’s plan to put humanoid robots to work by 2028 is not part of current negotiations with striking South Korean autoworkers, according to the company.
The automaker is disputing news reports that partial labor strikes by the Hyundai Motor union at the world’s largest automotive plant in South Korea were spurred by concerns about the company's planned deployment of humanoid robots in the United States starting in 2028. A company statement shared with Ars describes the union’s demands as focusing on compensation-related issues such as wage increases, bonuses, and an extension of workers’ retirement age.
“Potential deployment of robots in Korean production facilities is not part of the current labor-management discussions,” according to the Hyundai statement. “Hyundai Motor Company remains committed to constructive engagement with the union and to reaching an agreement that supports the long-term interests of both employees and the company.”
In the latest twist on battlefield innovations, Ukraine has used both flying drone carriers and drone boats to send ground robots armed with weapons or explosives into battle.
The drone-assisted deployments have enabled slower wheeled robots to bypass tough terrain and Russian defenses, and to carry out an unusual robotic amphibious assault on a contested position. Such tactics also showcase the Ukrainian military’s ongoing experimentation with using drones and robots to offset a Russian military advantage in manpower while also sparing Ukrainian soldiers from making dangerous assaults.
On July 19, a Russian military Telegram channel posted a video showing a Ukrainian hexacopter drone carrying a ground robot suspended below by a cable, according to the Ukrainian government-run news platform United24. The Russian Telegram channel described the Ukrainian heavy bomber drone as deploying a four-wheeled ARK-1 robot armed with explosive anti-tank mines on the ground where it continued toward Russian military positions—and apparently generated plenty of outraged comments from pro-Kremlin social media users.
Humanoid robots have surgically removed the gallbladders from living animals in an unprecedented medical experiment—but not as autonomous machines capable of replacing human doctors. Instead, skilled human surgeons remotely controlled the robots’ movements in a new example of human-robot teamups.
The teleoperated humanoid robots completed two minimally invasive surgeries by removing gallbladders from live pigs during a preclinical trial that was published in the journal Nature. If this approach eventually proves clinically ready for human patients, surgeons could use such humanoid robots to remotely perform robotic-assisted surgical care in smaller hospitals and clinics that lack the resources to install specialized but expensive surgical robots.
“It's a fraction of the cost and it takes a fraction of the space in an operating room,” said Shanglei Liu, an assistant professor of surgery at the University of California San Diego School of Medicine, in an interview with UC San Diego Today. “So it’s easy to deploy, anywhere from rural areas, to the battlefield, and even to space.”
South Korea’s government and top tech companies are committing $1 trillion to several flagship megaprojects that could bolster global memory chip supply, build new AI data centers, and spur commercial deployment of humanoid robots by 2028.
The announcement comes as South Korean companies such as Samsung and SK Hynix have enjoyed record profits and stock valuations due to the AI industry’s demand for memory chips—with the subsequent supply strain leading to memory chip shortages and higher prices for consumer electronics. Meanwhile, Hyundai Motor Company is racing to mass-manufacture humanoid robots developed by its subsidiary, Boston Dynamics, so that the robotic workers can start taking over certain laborious tasks in automotive factories and other workplaces.
“We must secure the core elements of AI faster than any other country,” said South Korean President Lee Jae Myung in a televised speech on June 29, as reported by BBC News and other media outlets. “Semiconductors, physical AI, and AI data centers are the triple axis for a great leap forward."
Dozens of new robot arms have been installed at General Motors’ flagship electric vehicle factory in Detroit—even as 1,300 workers remain out of work following what was supposed to be a temporary layoff. The latest automation push has spurred union pushback over a potentially existential issue for automakers and their workers.
General Motors installed approximately 50 robot arms at GM’s Factory Zero plant in Detroit, Michigan, according to reporting by Crain’s Detroit Business. Made by the Japanese robotics company FANUC, the robots are designed to help attach various components to vehicles during the assembly line process. But leaders at United Auto Workers (UAW), the primary US union for autoworkers, reacted with anger to the new robotic presence, given how GM has not yet called back any of the workers affected by supposedly temporary layoffs in March.
More than 1,000 union members are still “laid off indefinitely,” James Cotton, president of UAW Local 22, told The Detroit News. He said that the company could bring some of those members back to work instead of installing the 50 robots.
What happens when you give AI coding agents a lab full of robotic arms, some compute resources, and a “generous token budget” for teaching the robots various tasks? The agents can apparently figure out a training regimen that teaches the robots to successfully cut zip ties and even insert GPUs into thin sockets on motherboards.
That glimpse into how AI can act in a fully autonomous way to automate robot training was made possible by a new agent harness framework—software that wraps around AI models to enable their use of various tools while also providing capabilities such as memory, context, constraint, and feedback loops. That agentic harness, called ENPIRE, was developed by robotics researchers at the Nvidia GEAR (Generalist Embodied Agent Research) lab alongside collaborators from Carnegie Mellon University in Pittsburgh and the University of California, Berkeley.
“A part of our NVIDIA GEAR lab now self-improves tirelessly overnight,” wrote Jim Fan, director of AI at NVIDIA, in a LinkedIn post. “We just read the reports in the morning.”
Fully autonomous drones killed Russian soldiers during a battlefield test two years ago, according to a Ukrainian drone manufacturer. If true, the incident would represent another milestone in a war that has spurred unprecedented developments in military drones, robots, and AI-guided weaponry.
The one-time test was revealed by Alexander Kokhanovskyy, CEO of the Ukrainian drone maker Aero Center, during an interview with New Scientist at a press event hosted by the Ukrainian embassy in London. Kokhanovskyy described the test—which did not involve his current company Aero Center—using quadcopter drones that were preprogrammed to fly to a front-line area before activating an AI-powered “Terminator mode” that would seek out and attack any target in the given area.
There was apparently no video feed or anything else to show what the “Terminator” drones targeted and attacked. But Kokhanovskyy told New Scientist that human-piloted drones sent to check out the aftermath found “a couple” of dead Russian soldiers, which led to the conclusion that the fully autonomous drones had killed them.
A decade after the global craze for Pokémon Go peaked, an AI company has been using billions of real-world images captured by millions of players to develop navigation technologies for delivery robots and possibly military drones. That represents an intriguing but potentially discomfiting legacy for an augmented reality mobile game that has incentivized gamers to capture short smartphone videos of physical neighborhoods and landmarks.
The AI company, Niantic Spatial, was spun out of Pokémon Go game developer Niantic in May 2025, after Niantic separately sold its licensed games such as Pokémon Go to the Saudi-backed video game publisher Scopely. But before that deal, Niantic publicly announced plans to use scans from millions of Pokémon Go players along with data captured by users of the company’s Scaniverse app to train and develop a “large geospatial model”—a 3D model of the physical world trained on the geolocated images provided by app users scanning real-world locations.
“Ground scans were one component to help train Niantic Spatial's real-world foundation models —AI systems that learn to recognize and interpret physical spaces,” a Niantic Spatial spokesperson told Ars. “The models are the product of that training, not a copy of or a means of accessing the underlying scans, which were of public points of interest such as statues and fountains.”
It may appear that humanoid robots capable of handling any task have almost arrived—especially when tech companies showcase them performing acrobatic feats or handling household chores. But there is still a significant gap between these robot demonstrations and proving that the same robots can reliably and repeatedly manage such tasks in the real world.
The latest wave of robot videos can be particularly tricky, given the human tendency to anthropomorphize objects with a humanoid figure. A robot arm doing a dance move may simply seem “cool,” but a humanoid robot doing the same dance move can trigger more misleading assumptions, said Jonathan Hurst, cofounder of Agility Robotics and a robotics researcher at Oregon State University.
“People automatically extrapolate and assume that the robot that looks like a person can do all the things that a person who can dance could do—which is not true,” Hurst told Ars. “But a lot of the startup companies do kind of prey on that for being able to raise a lot of money.”
A San Francisco robotics startup is being taken to court by an Airbnb host who claims the company’s “robotic prototype testing” caused extensive damage to his home.
In the lawsuit filed on May 26, 2026, Sean Donovan is seeking more than $12,000 in damages from the Bay Area startup The Bot Company. The court case was first reported by SFGate, which also interviewed Donovan about the unprecedented mess he encountered after the startup’s employees supposedly rented his former childhood home through Airbnb.
The first clue that the guests were not typical tech startup employees needing a temporary crash pad came when Donovan was taking care of the trash during the guests’ stay. He told SFGate about seeing “bundles of wires” throughout the house and a robot he described as a 6-foot-tall “Roomba with treads” that also resembled the cybernetic Borg from the Star Trek universe.
A tech startup is offering New York City residents free home cleaning with a twist—it will send “professional cleaners” wearing cameras to record everything they do. All that data will supposedly be used to train AI-driven robots.
The unusual pitch comes from the German startup MicroAGI, whose website describes the company as a “team of engineers, researchers, and operators on a mission to accelerate embodied AI.” It began publicizing the free home-cleaning service run through its newly launched Shift app on May 28, with posts on social media sites such as X and LinkedIn featuring a video set to the upbeat piano notes of the Jay-Z and Alicia Keys song “Empire State of Mind.”
The Shift app website claims it “connects New Yorkers with free, trusted professional house cleaners” in exchange for recording “first-person cleaning footage to help train the next generation of household robots.” The “book a free cleaning” link directs clients to enter information such as a phone number, email address, and home address, along with access instructions, before booking an appointment that lasts an estimated two hours.
A $2,500 pair of humanoid robot legs built from 3D-printed parts and off-the-shelf components is not going to win marathons just yet. But such relatively inexpensive hardware could enable researchers to more easily test and train AI-powered robotics software in a physical body during real-world experiments.
The newly available LeRobot Humanoid project comes from the machine-learning and AI development platform Hugging Face. The full-stack release gives robot builders and researchers access to a bill of materials, files for 3D-printable parts, wiring documentation, and physical assembly instructions—but it also includes software tools for calibrating and controlling the robot in both the physical body and in simulation.
“If you are looking for the most advanced humanoid robot, this is not it,” wrote Virgile Batto, a robotics engineer at Hugging Face, in a blog post coauthored with other colleagues. “If you are looking for a humanoid you can build, understand, repair, instrument, simulate, and use for learning experiments, this is the robot we are trying to make.”
Humanoid robots are getting a new gig as baggage handlers and cargo loaders at Tokyo’s Haneda Airport—part of a Japan Airlines experiment to address a human labor shortage as airport visitor numbers have surged in recent years.
The demonstration, set to launch in May 2026, could eventually test humanoid robots in a wide range of airport tasks, including cleaning aircraft cabins and possibly handling ground support equipment such as baggage carts, according to a Japan Airlines press release. The trials are scheduled to run until 2028, which suggests that travelers flying into or out of Tokyo may spot some of the robots at work.
This marks the latest foray for humanoid robots after they have already begun pilot-testing in workplaces such as automotive factories and warehouses. Most robotic productivity so far has relied on robotic arms and similarly specialized robots that perform the same predictable tasks on assembly lines and in warehouses. By comparison, humanoid robots face a much stiffer challenge in dealing with more open and unpredictable work environments, and it remains to be seen whether the latest robotic software and hardware will be up to the task.
Humanoid robots outran the fastest human competitors while surpassing the human world record during a half-marathon event held in Beijing on April 19. The demonstration of fast-improving robotic speed and autonomy comes as China’s tech industry is rapidly scaling up mass production of humanoid robots to explore possible uses in the real world.
The fastest robot from Chinese smartphone-maker Honor notched a winning time of 50 minutes and 26 seconds while autonomously navigating the 13-mile (21-kilometer) route, according to the Global Times. That beat the human world record of 57 minutes and 20 seconds recently set by Ugandan long-distance runner Jacob Kiplimo during the Lisbon Half Marathon.
The winning robot design took inspiration from top human athletes by incorporating long legs measuring approximately 37 inches (95 centimeters) in length, said Du Xiaodi, a test development engineer for Honor, who spoke as a member of the winning team to The Associated Press and other publications. Xiaodi also described the robot as incorporating a custom liquid-cooling system—derived from similar cooling technology for consumer electronics—that could potentially be adapted for industrial applications.
Robots such as Boston Dynamics’ four-legged Spot can now accurately read analog thermometers and pressure gauges while roaming around factories and warehouses. Those improvements come courtesy of Google DeepMind’s newest robotic AI model that aims to enhance robotic capabilities for ‘embodied reasoning’ when interacting with physical environments.
The new Gemini Robotics-ER 1.6 model announced on April 14 performs as a “high-level reasoning model for a robot” that can plan and execute tasks, according to Google DeepMind. This model also unlocks the capability of accurately reading instruments such as complex gauges and doing visual inspections using sight glasses that provide a transparent window to peek inside tanks and pipes—a performance upgrade that came about through Google DeepMind’s ongoing collaboration with robotics company Boston Dynamics.
Boston Dynamics has a keen interest in testing both quadruped and humanoid robotic workers in a wide range of industrial facilities, including the automotive factories of the robotic company’s corporate owner, Hyundai Motor Group. The company’s robot “dog,” Spot, is being trialled as a robotic inspector that roams throughout industrial facilities to check up on everything. Such inspection duties require “complex visual reasoning” to interpret the multiple needles, liquid levels, container boundaries and tick marks, along with text, in various instruments.
Ukrainian ground robots and drones have demonstrated how to overcome a Russian military position by themselves while forcing the surrender of Russian soldiers, claimed Ukrainian President Volodymyr Zelenskyy. If true, that would represent a significant robotic milestone during the ongoing war that has already been significantly reshaped by drones—and it could offer lessons for how militaries worldwide may use robots and drones to do the dirtiest and most dangerous jobs in future conflicts.
The claim by Zelenskyy has not been independently verified but was accompanied by a promotional video in which he described Ukraine’s military robots as having completed over 22,000 missions in the last three months. Ukraine’s defense ministry also recently described a threefold increase in the Ukrainian military’s uncrewed ground vehicle missions over the last five months, with more than 9,000 robotic missions conducted in March, according to Scripps News. The growing robotic ground presence represents a new trend in a war that has become synonymous with drones.
Zelenskyy’s statement may refer to an event that occurred in the Kharkiv Oblast in northeastern Ukraine last year, according to The Independent. It referenced a statement by the Ukrainian 3rd Separate Assault Brigade detailing how the unit had used flying drones and “kamikaze” ground robots to attack fortified Russian frontline positions at that time. The brigade’s statement also described Russian soldiers as surrendering to one of the unit’s robots after abandoning the battered fortifications.
Robotic machine-learning company Generalist has announced GEN-1, a new physical AI system that it says "crosses into production-level success rates" on "a broad range of physical skills" that used to require the dexterity and muscle memory of human hands. Generalist is also touting the new model's ability to respond to disruptions by improvising new moves and "connect[ing] ideas from different places in order to solve new problems."
GEN-1 builds on Generalist's previous GEN-0 model, which the company touted in November as a proof of concept for the applicability of scaling laws in robotics training, showing how more pre-training data and compute time improve post-training performance. But while large language models have been able to effectively process trillions of words collectively written on the Internet as part of their training, robotic models don't have a similar, readily accessible source of quality data about how humans manipulate objects.
To help solve this problem, Generalist has relied on "data hands," a set of wearable pincers that capture micro-movements and visual information as humans perform manual tasks. Generalist now claims it has collected over half a million hours and "petabytes of physical interaction data" to help train its physical model.
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